Signal evaluation apparatus and signal evaluation method

ABSTRACT

There is provided a signal evaluation apparatus and signal evaluation method capable of consistently measuring an accurate bit error rate regardless of the distribution profile of the difference of likelihoods (difference metrics) of data sequences. In the signal evaluation apparatus for decoding data sequences by means of maximum likelihood decoding, at least one pair of paths between which a distance has a minimum value are selected by a path selector circuit  10.  With regard to the paths selected by the path selector circuit  10,  a difference metric obtained by a difference metric calculator circuit  9  is statistically processed by a μ- and σ-calculator circuit  13  to calculate a bit error rate. Then, the bit error rate is corrected by correction means ( 11, 12, 14 ) on the basis of the number of measurement samples of the paths selected by the path selector circuit  10  and the number of all samples.

BACKGROUND OF THE INVENTION

[0001] The present invention relates to a signal evaluation apparatusand signal evaluation method for evaluating a reproduction signal of arecording medium.

[0002] In recent years, according to the digitization of various sortsof information including image information and audio information, theamount of digital information has been rapidly increased. In accordancewith this, optical disks and optical disk apparatuses suitable forincrease in capacity and increase in density have been developed. Withthe development in density increase of the optical disks, reproductionsignals read from the optical disks have been degraded in quality, andthe evaluation of reproduction signals is important. The evaluation ofreproduction signals as described above is used for quality assurance inthe shipment stage of the optical disks or used for adjusting each partof optical disk apparatuses so that the reproduction signal has the bestquality.

[0003] Conventionally, jitter, bit error rate (BER) and the like havebeen used for the evaluation of optical disks or optical diskapparatuses, and Japanese Patent Laid-Open Publication No. HEI 10-21651discloses a signal evaluation apparatus appropriate for PRML (PartialResponse Maximum Likelihood), which has been used for the reproductionsignal processing of optical disk apparatuses.

[0004] The above-mentioned signal evaluation apparatus will be describedbelow with reference to the drawings.

[0005] Reference is first made to the case where a reproduction signalis decoded by the aforementioned signal evaluation apparatus accordingto the Viterbi decoding system. A (1,7) RLL code that has a minimum runlength limited to one is adopted, and PR (1,2,1) is adopted as a PRMLsystem. The relation between a record bit sequence bk and a state Sk atthe time point of sample k (k=0, 1, 2, 3) assumes four states S0, S1, S2and S3 as shown in Table 1. TABLE 1 State Record Bit S_(k) b_(k−1) b_(k)S0 0 0 S1 0 1 S2 1 1 S3 1 0

[0006] Each state transits to the next state according to the nextrecord bit, and this state transition is called the “branch”.

[0007] Table 2 shows the relation between the record bit and the statetransition, and the number of branches is six because the minimum runlength is limited to one. TABLE 2 Expected Record Bit State Value No.b_(k−2) b_(k−1) b_(k) S_(k−1) S_(k) Y_(k) a 0 0 0 S0 S0 −1.0 b 1 0 0 S3S0 −0.5 c 0 0 1 S0 S1 −0.5 d 0 1 1 S1 S2 0.5 e 1 1 1 S2 S2 1.0 f 1 1 0S2 S3 0.5

[0008] According to PR (1,2,1), the reproduction signal level isdetermined by a 3-bit record bit sequence. Therefore, the expectedvalue, i.e., the reproduction signal level with an ideal waveform freeof noise is expressed as an expected value Yk in Table 2. In Table 2,the minimum value and the maximum value of the reproduction signal levelwith the ideal waveform are standardized to −1 and 1, respectively.

[0009] In this case, the branch metric (Zk−Yk)² of each branch at thetime point of sample k is calculated. Zk is the reproduction signallevel at the time point of sample k. This “branch metric”, which is thesquare of the difference between the reproduction signal level and theexpected value, therefore means the square error of the reproductionsignal level with respect to the expected value. The branch metric isused for determining which branch is to be selected when two branchesconverge into a certain state. Then, a continuous series of branches iscalled the “path”, and a continuous series of selected branches iscalled the “survival path”.

[0010] Assuming that the cumulative value of the branch metrics for thesurvival path in each state at the time of sample k−1 is m_(k−1), thenthe sum of the value m_(k−1) and the branch metric bm_(k) at the timepoint of sample k becomes the cumulative total value of the branchmetrics at the time point of sample k.

[0011] As described above, since the branch metric means the squareerror, the cumulative total value of the branch metrics is the sum totalof errors. Therefore, the branch of the smaller value of(m_(k−1)+bm_(k)) is selected.

[0012] For example, the branches whose states become S0 at the timepoint of sample k, are the two of the branch that transits from S0 to S0and the branch that transits from S3 to S0 according to Table 2. It ispostulated that the cumulative values of the branch metrics are m0_(k−1)and m3_(k−1) and the branch metrics are bma_(k) and bmb_(k).Accordingly, assuming that the cumulative total values of the branchmetrics at the time point of sample k are m0_(k)(a) and m0_(k)(b),respectively, then there hold the equations (1) and (2):

M0_(k)(a)=m0_(k−1) +bma _(k)  (1)

m0_(k)(b)=m3_(k−1) +bmb _(k)  (2)

[0013] Further, m0_(k)(a) and m0_(k)(b) are compared in magnitude witheach other, and the branch of the smaller one is selected.

[0014] In this case, if the correct state at the time point of sample kis S0 and the correct transition is a, then there is executed thecalculation of the equation (3):

Δm _(k) =m0_(k)(b)−m0_(k)(a)  (3)

[0015] and this Δm_(k) is called the “difference metric”.

[0016] Moreover, if the correct state at the time point of sample k isS0 and the correct transition is b, then the difference metric ΔM_(k) isexpressed by the equation (4)

Δm _(k) =m0_(k)(a)−m0_(k)(b)  (4)

[0017] That is, the cumulative total value of the branch metrics of thecorrect transition is subtracted from the cumulative total value of thebranch metrics of the erroneous transition. To know the correct stateand the correct transition, Japanese Patent Laid-Open Publication No.HEI 10-21651 discloses a method for using the recorded data sequence anda method for delaying the reproduced data sequence when the error rateof the reproduced data sequence is low.

[0018] In this case, if the branch to be selected as a result ofdecoding is the correct branch, then the difference metric Δm_(k) has apositive value. However, if an erroneous branch is selected, thedifference metric has a negative value.

[0019]FIG. 3 shows the distribution of the difference metrics calculatedat each sample time point. Postulating that the normal distribution hasa mean value μ and a standard deviation σ on the assumption that thedistribution profile can be approximated to the normal distribution,then the probability that the difference metric will become negative isequal to a bit error rate (BER) since the difference metric becomesnegative in the case of an error as described hereinbefore. That is, byexecuting a calculation according to the equation (5): $\begin{matrix}{{BER} = {\frac{1}{\sqrt{2\pi} \cdot \sigma}{\int_{- \infty}^{0}{^{\frac{{({t - \mu})}^{2}}{2\sigma^{2}}}{t}}}}} & (5)\end{matrix}$

[0020] the bit error rate BER can be estimated. Moreover, when it isonly required to know the relative quality of the bit error rate BER ofan optical disk or an optical disk apparatus instead of the absolutevalue of the bit error rate BER, it is acceptable to use σ/μ as anindex.

[0021]FIG. 3 shows a distribution that has a single peak. However, whenthere is a limitation on the minimum run length, there is a distributionthat has a plurality of peaks as shown in FIG. 4. Even in this case,assuming that the difference metric distribution conforms to the normaldistribution in the region where the difference metric is smaller thanthe value expressed by the mean value μ shown in FIG. 4 paying attentiononly to the distribution that has a peak position located nearest tozero, then the bit error rate BER can be calculated similarly to thedistribution that has a single peak. However, dissimilarly to thedistribution that has a single peak, the mean value μ cannot be obtainedfrom the arithmetic mean. Moreover, if the mean value μ is not obtained,then the standard deviation σ cannot be calculated.

[0022] In order to solve this problem, the aforementioned signalevaluation apparatus extracts only the sequence of which the differencemetric comes to have the highest probability of becoming negative, i.e.,the sequence that passes through the path that forms a distribution thathas a peak position located nearest to zero (hereinafter referred to asa “minimum distribution”). In paths as described above, a distancebetween the two paths has a minimum value, and there are four pathsaccording to this explanation. Table 3 shows four sequences that formthe minimum distribution.

[0023] By executing this processing, the distribution that has a singlepeak as shown in FIG. 3 is obtained, and both the mean value μ and thestandard deviation a can be calculated comparatively easily. TABLE 3State No. S_(k−3) S_(k−2) S_(k−1) S_(k) A S0 S0 S1 S2 B S0 S1 S2 S2 C S2S2 S3 S0 D S2 S3 S0 S0

[0024] As described above, by extracting only the sequence that passesthrough a prescribed path from the data sequence, the aforementionedsignal evaluation apparatus can obtain the distribution that has asingle peak.

[0025] However, the aforementioned signal evaluation apparatus extractsonly part of the whole data sequence, and therefore, only the bit errorrate of part of all the data can be calculated from the obtaineddistribution. In other words, there is a problem that the aforementionedsignal evaluation apparatus cannot obtain the accurate bit error rate ofthe whole data sequence although the correct bit error rate is the ratioof the number of errors to the number of all the samples.

[0026] Since the minimum distribution has a peak position locatednearest to zero, it can be considered that almost all the errors occurin the data sequence included in this distribution. Even though thenumber of generated errors is same, the bit error rate BER is variedwhen the number of all the samples is varied.

[0027] For example, assuming that the number of error is one and thenumber of samples included in the minimum distribution is 10000, thenthe error rate of the minimum distribution is 1×10⁻⁴. In this case, ifthe number of all the measurement samples is equal to the number ofsamples of the minimum distribution, then the bit error rate BER alsobecomes 1×10⁻⁴. However, if the number of all the samples is 100000,then the bit error rate BER is 1×10⁻⁵. As described above, even if thenumber of generated errors is same, the bit error rate BER is varieddepending on the ratio of the number of samples included in the minimumdistribution to the number of all the samples. The ratio of the numberof samples included in the minimum distribution with respect to thenumber of all the samples varies according to the data pattern to berecorded, and the distribution profile of the difference metrics shownin FIG. 4 also varies.

SUMMARY OF THE INVENTION

[0028] Accordingly, the object of the present invention is to provide asignal evaluation apparatus and signal evaluation method capable ofalways measuring the accurate bit error rate regardless of thedistribution profile of the difference of the likelihoods (differencemetrics) of data sequences.

[0029] In order to achieve the aforementioned object, there is provideda signal evaluation apparatus for decoding data sequences by means ofmaximum likelihood decoding, comprising:

[0030] a subtraction means for obtaining a difference of likelihoods ofat least one pair of paths of the data sequences;

[0031] a selection means for selecting from the data sequences at leastone pair of paths between which a distance has a minimum value;

[0032] a calculation means for executing statistical processing of thedifference of likelihoods obtained by the subtraction means with regardto the paths selected by the selection means; and

[0033] a correction means for correcting results of the statisticalprocessing executed by the calculation means on the basis of the numberof measurement samples of the paths selected by the selection means andthe number of all samples of the data sequences.

[0034] According to the signal evaluation apparatus of theabove-mentioned construction, the paths between which a distance has aminimum value are selected from the data sequences by the selectionmeans. The paths between which a distance has a minimum value are a pairof paths that diverge from a certain state and subsequently convergeearliest in the shortest distance. For the paths between which adistance has a minimum value among the data sequences selected by theselection means, the difference of likelihoods obtained by thesubtraction means is statistically processed by the calculation means.The difference of likelihoods of the selected paths forms a minimumdistribution. By statistically processing the difference of likelihoodsof the selected paths, it is enabled to obtain the mean value and thestandard deviation of the minimum distribution as well as the results ofstatistical processing of the bit error rate and so on from the meanvalue and the standard deviation. Then, by correcting the results of thestatistical processing executed by the calculation means, on the basisof the number of all the samples of the data sequences and the number ofthe measurement samples of the paths selected by the selection means,the results of the statistical processing of all the data of the datasequences can be obtained. Therefore, the accurate bit error rate canconsistently be measured regardless of the distribution profile of thedifference of likelihoods (difference metrics) of the data sequences.

[0035] Moreover, according to one embodiment, the correction meanscomprises:

[0036] a first counting means for counting the number of measurementsamples of the paths selected by the selection means;

[0037] a second counting means for counting the number of all thesamples of the data sequences; and

[0038] a bit error rate correction means for correcting a bit errorrate, which is a result of the statistical processing executed by thecalculation means, on the basis of the number of measurement samplescounted by the first counting means and the number of all the samples ofthe data sequences counted by the second counting means.

[0039] According to the above-mentioned embodiment, by correcting thebit error rate, which is the result of the statistical processingexecuted by the calculation means, on the basis of the number ofmeasurement samples, counted by the first counting means, of the pathsselected by the selection means and the number of all the samples of thedata sequences counted by the second counting means, the bit error rateof all the data of the data sequences is easily obtained.

[0040] Moreover, according to one embodiment,

[0041] assuming that the number of measurement samples counted by thefirst counting means is To and the number of all the samples of the datasequences counted by the second counting means is T,

[0042] then the bit error rate correction means corrects the bit errorrate according to the equation:

BER1=BER0·To/T

[0043] where

[0044] BER1 is a bit error rate after correction,

[0045] BER0 is a bit error rate before correction,

[0046] To is the number of samples of at least one pair of paths betweenwhich a distance is minimized, and

[0047] T is the number of all samples.

[0048] According to the above-mentioned embodiment, the bit error ratecorrection means is able to execute the correction operation of the biterror rate easily in a short time by using the above-mentioned equation.

[0049] The present invention provides a signal evaluation method fordecoding a data sequence by means of maximum likelihood decoding,comprising the steps of:

[0050] extracting only a data sequence, which passes through aprescribed path, from data sequences;

[0051] calculating a bit error rate of the extracted data sequence; and

[0052] calculating a bit error rate of all data of the data sequences bycorrecting the bit error rate calculated for the extracted data sequenceon the basis of the number of samples of the extracted data sequence andthe number of all samples of the data sequences.

[0053] According to the above-mentioned signal evaluation method, onlythe data sequence that passes through the prescribed path is extractedfrom the data sequences, and the bit error rate is calculated for theextracted data sequence. For example, only the data sequence, whichpasses through the path of the data sequence that forms the minimumdistribution as a prescribed path, is extracted, and the bit error rateof the minimum distribution is obtained from the statistical processingresults (mean value and standard deviation) of the difference oflikelihoods of the extracted paths. Subsequently, the bit error rate ofall the data of the data sequences is calculated by correcting the biterror rate calculated for the extracted data sequence on the basis ofthe number of samples of the extracted data sequence and the number ofall the samples of the data sequences. Therefore, the accurate bit errorrate can consistently be measured regardless of the distribution profileof the difference of likelihoods (difference metrics) of the datasequences.

[0054] The present invention provides a signal evaluation apparatus fordecoding a data sequence by means of maximum likelihood decoding,comprising:

[0055] a data sequence extraction means for extracting only a datasequence that passes through a prescribed path, from data sequences;

[0056] a bit error rate calculation means for calculating a bit errorrate of the data sequence extracted by the data sequence extractionmeans; and

[0057] a bit error rate correction means for calculating a bit errorrate of all data of the data sequences by correcting the bit error ratecalculated by the bit error rate calculation means on the basis of thenumber of samples of the data sequence extracted by the data sequenceextraction means and the number of all samples of the data sequences.

[0058] According to the above-mentioned signal evaluation apparatus,only the data sequence that passes through the prescribed path isextracted from the data sequences by the data sequence extraction means,and the bit error rate for the extracted data sequence is calculated bythe bit error rate calculation means. For example, only the datasequence, which passes through the path of the data sequence that formsthe minimum distribution as a prescribed path, is extracted, and the biterror rate of the minimum distribution is obtained from the statisticalprocessing results (mean value and standard deviation) of the differenceof likelihoods of the extracted paths. Subsequently, the bit error rateof all the data of the data sequences is calculated by correcting thebit error rate by the bit error rate correction means on the basis ofthe number of samples of the extracted data sequence and the number ofall the samples of the data sequences. Therefore, the accurate bit errorrate can consistently be measured regardless of the distribution profileof the difference of likelihoods (difference metrics) of the datasequences.

BRIEF DESCRIPTION OF THE DRAWINGS

[0059] The present invention will become more fully understood from thedetailed description given hereinbelow and the accompanying drawingswhich are given by way of illustration only, and thus are not limitativeof the present invention, and wherein:

[0060]FIG. 1 is a schematic diagram showing an essential part of areproduction signal processing section of an optical disk apparatus thatemploys a signal evaluation apparatus according to one embodiment ofthis invention;

[0061]FIG. 2 is a flowchart of the above signal evaluation apparatus;

[0062]FIG. 3 is an explanatory view showing a difference metricdistribution; and

[0063]FIG. 4 is an explanatory view showing a difference metricdistribution when there is a limitation on the minimum run length.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

[0064] The signal evaluation apparatus and signal evaluation method ofthis invention will be described in detail below on the basis of theembodiment shown in the drawings.

[0065]FIG. 1 is a schematic diagram of the essential part of areproduction signal processing section of an optical disk apparatusemploying a signal evaluation apparatus according to one embodiment ofthis invention. In this embodiment, an optical disk is used as arecording medium, and a reproduction signal is decoded by a Viterbidecoding system. The (1,7) RLL code that has a minimum run lengthlimited to one is adopted, and PR (1,2,1) is adopted as a PRML system.

[0066] In FIG. 1 are shown an optical disk 1, a spindle motor 2 forrotatively driving the optical disk 1, an object lens 3, an opticalpickup 4, an RF circuit 5 for adjusting the amplitude and so on of a MOsignal (Magneto Optical signal) from the optical pickup 4, an A/Dconverter 6 for subjecting the MO signal from the RF circuit 5 to A/D(analog-to-digital) conversion, a decoder circuit 7 for decoding digitaldata from the A/D converter 6 by means of maximum likelihood decoding,an error correction circuit 8 for executing error correction of the datadecoded by the decoder circuit 7, a difference metric calculator circuit9 that serves as a subtracting means for obtaining the difference metricof the recorded data sequence decoded by the decoder circuit 7, a pathselector circuit 10 that serves as a selecting means for selecting apath from the whole data sequence on the basis of the difference metricobtained by the difference metric calculator circuit 9 and a statetransition signal from the decoder circuit 7, a first counter 11 thatserves as a second counting means for cumulatively counting the numberof all the samples decoded by the decoder circuit 7, a second counter 12that serves as a first counting means for cumulatively counting thenumber of samples of the path selected by the path selector circuit 10,a μ- and σ-calculator circuit 13 that serves as a calculating means forstatistically processing the difference metric of the path selected bythe path selector circuit 10, a controller 14 that serves as acorrection operation means and a record data generator 15. The firstcounter 11, the second counter 12 and the controller 14 constitute acorrection means. The path selector circuit 10 serves as a data sequenceextraction means, and the controller 14 serves as a bit error ratecalculation means and a bit error rate correction means. It is to benoted that a magneto-optical disk is herein used as the optical disk 1although there is a variety of optical disks.

[0067] In the optical disk apparatus of the above-mentionedconstruction, a beam of light converged by the object lens 3 providedfor the optical pickup 4 is applied from below to the recording surfaceof the optical disk 1. Then, the light reflected on the recordingsurface of the optical disk 1 is detected by a photodetector providedinside the optical pickup 4, and the reflected light is separated intoan MO signal (Magneto Optical signal) and other signals.

[0068] The MO signal detected by the optical pickup 4 is subjected toadjustment of amplitude and offset by the RF circuit 5 and thereafterconverted into digital data by the A/D converter 6. The digital dataoutputted from the A/D converter 6 is supplied to the decoder circuit 7,and the decoder circuit 7 executes decoding according to the PRMLsystem.

[0069] Next, the data decoded by the decoder circuit 7 is transferred tothe error correction circuit 8, and the error correction circuit 8executes error detection and correction by means of the error detectioncorrection code that has preparatorily been added into the decoded data.The output of this error correction circuit 8 is supplied to thecontroller 14.

[0070] Record data sequence information obtained through the decodingprocess by the PRML system in the decoder circuit 7 is supplied to thedifference metric calculator circuit 9. In order to count the number ofsamples of the data decoded by the decoder circuit 7 by the firstcounter 11, one pulse is supplied from the decoder circuit 7 to thefirst counter 11 every time one sample is decoded. Thus, the number ofall the decoded samples is cumulatively counted by the first counter 11.

[0071] In the difference metric calculator circuit 9, the same operationas described in connection with the conventional signal evaluationapparatus is executed.

[0072] That is, the decoder circuit 7 decodes the reproduction signal ofthe optical disk 1 according to the Viterbi decoding system. In thiscase, reference is made to the case where the (1,7) RLL code that has aminimum run length limited to one is adopted as a code to be used and PR(1,2,1) is adopted as the PRML system. The relation between a record bitsequence bk and a state S_(k) at the time point of sample k isclassified into four states S0, S1, S2 and S3 as shown in Table 4. TABLE4 State Record Bit S_(k) b_(k−1) b_(k) S0 0 0 S1 0 1 S2 1 1 S3 1 0

[0073] Each state transits to the next state according to the nextrecord bit. This state transition is called the branch. Table 5 showsthe relation between the record bit and the state transition. Asdescribed hereinbefore, the (1,7) RLL code that has a minimum run lengthlimited to one is adopted as a code to be used. That is, the minimum runlength is limited to one, and therefore, the number of branches is thesix of a, b, c, d, e and f. TABLE 5 Expected Record Bit State Value No.b_(k−2) b_(k−1) b_(k) S_(k−1) S_(k) Y_(k) a 0 0 0 S0 S0 −1.0 b 1 0 0 S3S0 −0.5 c 0 0 1 S0 S1 −0.5 d 0 1 1 S1 S2 0.5 e 1 1 1 S2 S2 1.0 f 1 1 0S2 S3 0.5

[0074] According to PR (1,2,1), the reproduction signal level isdetermined by a 3-bit record bit sequence. Therefore, the expectedvalue, i.e., the reproduction signal level with the ideal waveform freeof noise is entered as an expected value Yk in Table 5. In this case,the minimum value and the maximum value of the reproduction signal levelwith the ideal waveform are standardized to −1 and 1, respectively.

[0075] Then, through the PRML decoding process, the decoder circuit 7calculates the branch metric (Zk−Yk)² of each branch at the time pointof sample k. In this case, Zk represents the reproduction signal levelat the time point of sample k, and Yk represents the expected value ofthe reproduction signal level. As described above, the branch metric,which is the square of the difference between the reproduction signallevel and the expected value, therefore means the square error of thereproduction signal level with respect to the expected value.

[0076] Then, the branch metric is used for determining which branch isto be selected when two branches converge into a certain state. Then, acontinuous series of branches is called the path, and a continuousseries of the selected branches is called the survival path.

[0077] Assuming herein that the cumulative value of the branch metricsof the survival path in each state is m_(k−1) at the time of sample k−1,then the sum of the value and the branch metric bm_(k) at the time pointof sample k becomes the cumulative total value of the branch metrics atthe time point of sample k. The arithmetic processing to the obtainmentof this branch metric is executed by the decoder circuit 7.

[0078] As described above, the branch metric means the square error, andtherefore, the cumulative total value is the sum total of errors.Therefore, the branch of the smaller value of m_(k−1)+bm_(k) isselected.

[0079] For example, the branches that come to have the state S0 at thetime point of sample k are the two branches of the branch “a” thattransits from S0 to S0 and the branch “b” that transits from S3 to S0according to Table 5. Assuming that the cumulative values of the branchmetrics of the branch “a” and the branch “b” are m0_(k−1) and m3_(k−1),respectively, and their branch metrics are bma_(k) and bmb_(k), then thecumulative total values m0_(k)(a) and m0_(k)(b) of the branch metric “a”and the branch metric “b” at the time point of sample k are expressed bythe following equations (1) and (2):

M0_(k)(a)=m0_(k−1) +bma _(k)  (1)

m0_(k)(b)=m3_(k−1) +bmb _(k)  (2)

[0080] Further, m0_(k)(a) and m0_(k)(b) are compared in magnitude witheach other, and the branch of the smaller value is selected.

[0081] Herein, when the correct state at the time point of sample k isS0 and the correct transition is a, there is executed the calculation ofthe equation (3):

Δm _(k) =m0_(k)(b ⁾⁻ m0_(k)(a)  (3)

[0082] and this Δm_(k) is called the “difference metric”.

[0083] When the correct state at the time point of sample k is S0 andthe correct transition is b, the difference metric (Δm_(k)) is expressedby the equation (4):

Δm _(k) =m0_(k)(a)−m0_(k)(b)  (4)

[0084] That is, the difference metric calculator circuit 9 executes theprocessing of obtaining the difference metric as a difference oflikelihoods by subtracting the cumulative total value of the branchmetrics of the correct transition from the cumulative total value of thebranch metrics of the erroneous transition.

[0085] In the present embodiment, record data sequence informationnecessary for the calculation in the difference metric calculatorcircuit 9 is supplied from the record data generator 15 to thedifference metric calculator circuit 9.

[0086] Then, the difference metric obtained by the difference metriccalculator circuit 9 is supplied to the path selector circuit 10.

[0087] Moreover, a state transition signal is supplied as informationfor path selection from the decoder circuit 7 to the path selectorcircuit 10, and the path selector circuit 10 selects four paths (thedistance between the pair of the paths has a minimum value) shown inTable 3 from the whole data sequences. Then, for the paths that coincidewith the four paths shown in Table 3, the path selector circuit 10supplies the difference metrics of the samples included in thecoinciding paths to the μ- and σ-calculator circuit 13. At the sametime, the same number of pulses as the number of samples of the pathsthat coincide with the four paths shown in Table 3 are supplied to thesecond counter 12. Thus, the number of samples of the paths selected bythe path selector circuit 10 is cumulatively counted by the secondcounter 12.

[0088] The μ- and σ-calculator circuit 13 calculates the mean value μand the standard deviation σ of the difference metrics for the pathsselected by the path selector circuit 10.

[0089] Then, the results of counting executed by the first counter 11and the second counter 12 and the results of calculation executed by theμ- and σ-calculator circuit 13 are processed by the software of thecontroller 14.

[0090]FIG. 2 shows a flowchart of the entire measurement processing fromthe start of measurement to the obtainment of measurement results.

[0091] First of all, prior to the measurement, the count values of thefirst and second counters 11 and 12 are cleared to zero in step 1.

[0092] Next, the program flow proceeds to step 2 to start the decodingprocess by reading a prescribed region of the disk 1.

[0093] Subsequently, the program flow proceeds to step 3 to determinewhether or not the measurement ends and perform measurement for aprescribed period by repeating the step 3 until the measurement ends.During this measurement period, there is executed measurement by thedifference metric calculator circuit 9, the path selector circuit 10,the μ- and σ-calculator circuit 13 and the first and second counters 11and 12. If the measurement ends, then the program flow proceeds to step4 to end the decoding process.

[0094] Next, the program flow proceeds to step 5 to read the number T ofall the samples counted by the first counter 11, the number To of themeasurement samples counted by the second counter 12 and the mean valueμ and the standard deviation σ calculated by the μ- and σ-calculatorcircuit 13.

[0095] Next, the program flow proceeds to step 6 to obtain a bit errorrate BER0 before correction from the mean value μ and the standarddeviation σ obtained in step 5 according to the following equation (6):$\begin{matrix}{{{BER}\quad 0} = {\frac{1}{\sqrt{2\pi} \cdot \sigma}{\int_{- \infty}^{0}{^{\frac{{({t - \mu})}^{2}}{2\sigma^{2}}}{t}}}}} & (6)\end{matrix}$

[0096] The bit error rate BER0 obtained here is the bit error rate ofthe data sequence that forms a minimum distribution.

[0097] Next, the program flow proceeds to step 7 to execute thecorrection operation of the bit error rate. This correction operationconverts the bit error rate BER0 obtained in step 6 into a bit errorrate BER1 of the whole data sequences according to the followingequation (7):

BER1=BER0·To/T  (7)

[0098] As described above, the bit error rate of the whole datasequences is calculated by obtaining the bit error rate of the minimumdistribution from the mean value μ and the standard deviation σ of thedifference metrics of the data sequence that forms a minimumdistribution and executing the correction operation of the bit errorrate.

[0099] In the above-mentioned embodiment, the number To of themeasurement samples and the number T of all the samples are counted bythe first and second counters 11 and 12. However, when the number ofsamples per sector is determined by the format of a recording medium, itis possible to execute the correction operation of the bit error rate bysetting the measurement period in sectors without counting the number Tof all the samples.

[0100] For example, assuming that one sector has 10000 samples and dataof two sectors are measured, then the number T of all the samples become20000 samples. By so doing, the first counter 11 can be removed, and theconstruction of the apparatus can be simplified. If it is enabled tocount the number T of all the samples by a counter, then a regionsmaller than one sector can be measured, producing an advantage thatprecise evaluation of high positional resolution becomes possible.Therefore, it is proper to make appropriate selection taking thesimplification of the apparatus construction and the requiredmeasurement resolving power into consideration.

[0101] It is further acceptable to provide the recording surface of theoptical disk with a test region for making an evaluation and record aprescribed test data pattern in the test region. Since the ratio of theminimum distribution to all the data included in this test data patternis already known, there is no need for counters for counting the numberT of all the samples and the number To of the measurement samples. Inthis case, there is a disadvantage that the region usable by the user isreduced because of the necessity of the special test area, and it is notpossible to make an evaluation in an arbitrary place.

[0102] As described above, because the bit error rate BER of all thedata is calculated by obtaining the bit error rate BER of the minimumdistribution from the mean value μ and the standard deviation σ of thedifference metrics of the data sequence that forms a minimumdistribution and executing the correction operation of the bit errorrate of the minimum distribution, the accurate bit error rate BER canconsistently be measured regardless of the distribution profile of thedifference metrics of the data sequence.

[0103] In the above-mentioned embodiment, the magneto-optical diskreproduction apparatus using the signal evaluation apparatus and thesignal evaluation method has been described. However, the presentinvention is not limited to this, and it is acceptable to apply thesignal evaluation apparatus and signal evaluation method of thisinvention to a magnetic recording apparatus, a communication datareception apparatus or the like, which decodes data sequences using themaximum likelihood decoding.

[0104] As is apparent from the above, according to the signal evaluationapparatus and signal evaluation method of this invention, the bit errorrate of all the data of the data sequences can be obtained by obtainingthe bit error rate of the minimum distribution from the statisticalprocessing results (mean value μ and standard deviation σ) of thedifference of likelihoods (difference metrics) of the data sequencesthat form the minimum distribution and executing the correctionoperation of the error rate. Therefore, the accurate bit error rate canconsistently be measured regardless of the distribution profile of thedifference of likelihoods (difference metrics) of the data sequences.

[0105] The invention being thus described, it will be obvious that thesame may be varied in many ways. Such variations are not to be regardedas a departure from the spirit and scope of the invention, and all suchmodifications as would be obvious to one skilled in the art are intendedto be included within the scope of the following claims.

What is claimed is:
 1. A signal evaluation apparatus for decoding datasequences by means of maximum likelihood decoding, comprising: asubtraction means for obtaining a difference of likelihoods of at leastone pair of paths of the data sequences; a selection means for selectingfrom the data sequences at least one pair of paths between which adistance has a minimum value; a calculation means for executingstatistical processing of the difference of likelihoods obtained by thesubtraction means with regard to the paths selected by the selectionmeans; and a correction means for correcting results of the statisticalprocessing executed by the calculation means on the basis of the numberof measurement samples of the paths selected by the selection means andthe number of all samples of the data sequences.
 2. The signalevaluation apparatus as claimed in claim 1, wherein the correction meanscomprises: a first counting means for counting the number of measurementsamples of the paths selected by the selection means; a second countingmeans for counting the number of all the samples of the data sequences;and a bit error rate correction means for correcting a bit error rate,which is a result of the statistical processing executed by thecalculation means, on the basis of the number of measurement samplescounted by the first counting means and the number of all the samples ofthe data sequences counted by the second counting means.
 3. The signalevaluation apparatus as claimed in claim 2, wherein, assuming that thenumber of measurement samples counted by the first counting means is Toand the number of all the samples of the data sequences counted by thesecond counting means is T, then the bit error rate correction meanscorrects the bit error rate according to the equation: BER1=BER0·To/Twhere BER1 is a bit error rate after correction, BER0 is a bit errorrate before correction, To is the number of samples of at least one pairof paths between which a distance is minimized, and T is the number ofall samples.
 4. A signal evaluation method for decoding a data sequenceby means of maximum likelihood decoding, comprising the steps of:extracting only a data sequence, which passes through a prescribed path,from data sequences; calculating a bit error rate of the extracted datasequence; and calculating a bit error rate of all data of the datasequences by correcting the bit error rate calculated for the extracteddata sequence on the basis of the number of samples of the extracteddata sequence and the number of all samples of the data sequences.
 5. Asignal evaluation apparatus for decoding a data sequence by means ofmaximum likelihood decoding, comprising: a data sequence extractionmeans for extracting only a data sequence that passes through aprescribed path, from data sequences; a bit error rate calculation meansfor calculating a bit error rate of the data sequence extracted by thedata sequence extraction means; and a bit error rate correction meansfor calculating a bit error rate of all data of the data sequences bycorrecting the bit error rate calculated by the bit error ratecalculation means on the basis of the number of samples of the datasequence extracted by the data sequence extraction means and the numberof all samples of the data sequences.